Collaborative Task Execution With Humans And Robotic Vehicles

ABSTRACT

Methods and systems for joint execution of complex tasks by a human and a robotic system are described herein. In one aspect, a collaborative robotic system includes a payload platform having a loading surface configured to carry a payload shared with a human collaborator. The collaborative robotic system navigates a crowded environment, while sharing a payload with the human collaborator. In another aspect, the collaborative robotic system measures forces in a plane parallel to the loading surface of the payload platform to infer navigational cues from the human collaborator. In some instances, the collaborative robotic system overrides the navigational cues of the human collaborator to avoid collisions between an object in the environment and any of the robotic system, the human collaborator, and the shared payload.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application for patent claims priority under 35 U.S.C. § 119from U.S. provisional patent application Ser. No. 62/639,995, entitled“Collaborative Carrying With Humans And Robotic Vehicles,” filed Mar. 7,2018, the subject matter of which is incorporated herein by reference inits entirety.

TECHNICAL FIELD

The described embodiments relate to systems and methods for payloadtransport in a service environment.

BACKGROUND INFORMATION

Robotic systems are widely deployed to perform highly repetitive tasks,typically in a well-controlled, factory environment. In some examples offactory automation, a robot performs a single task repeatedly for longperiods of time (e.g., months or years). However, the robotic systemsare not yet widely deployed to perform tasks that are part of theeveryday lives of humans. To better integrate robotic systems into theeveryday lives of humans as well as custom workflows, robotic systemsmust be able to adapt to new tasks and environmental conditions.

In some examples, robotic systems have been developed with increasedintelligence to enable robotic systems to perform a wide range of tasksin unstructured environments. Intelligent robotic systems are able tobetter comprehend complex tasks and execute the task at hand with lessinstruction. In addition, improved user interfaces enhance communicationbetween humans and a robotic system; enabling the collaborative roboticsystem to better understand the task at hand. Recent improvements touser interfaces include the use of natural user interfaces and the useof speech and gesture based technologies to improve usability of robots.However, these approaches focus on communicating task goals andconstraints to the collaborative robotic system for execution solely bythe robotic system. This limits the complexity of the task that can beaccomplished by the robotic system due to limitations in the physicaland intellectual capability of the robotic system and limitations in theability to communicate task parameters and constraints to the roboticsystem.

In summary, improvements to robotic systems are desired to enableexecution of complex tasks in highly unstructured environments.

SUMMARY

Methods and systems for collaboration between humans and robotic systemsto jointly execute complex tasks are described herein. Collaborativetask execution takes advantage of the adaptability of humans and enablesmore effective use of a collaborative robotic system that wouldotherwise be limited to the execution of less complex tasks.

In one aspect, a collaborative robotic system includes a payloadplatform having a loading surface configured to carry a payload sharedwith a human collaborator.

In another aspect, load sensors of a collaborative robotic systemmeasure forces in a plane parallel to the loading surface of the payloadplatform. The collaborative robotic system infers navigational cues froma human collaborator based on the measured forces.

In another aspect, a collaborative robotic system includes one or moreproximity sensors configured to estimate the proximity of objects to therobotic system.

In another aspect, a collaborative robotic system navigates a crowdedenvironment, while sharing a payload with a human collaborator. In someinstances, the collaborative robotic system overrides the navigationalcues of the human collaborator to avoid collisions between an object inthe environment and any of the robotic system, the human collaborator,and the shared payload.

The foregoing is a summary and thus contains, by necessity,simplifications, generalizations, and omissions of detail; consequently,those skilled in the art will appreciate that the summary isillustrative only and is not limiting in any way. Other aspects,inventive features, and advantages of the devices and/or processesdescribed herein will become apparent in the non-limiting detaileddescription set forth herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrative of an embodiment of a collaborativerobotic system 100 including a wheeled, robotic vehicle and payloadplatform in side view.

FIG. 2 is a diagram illustrative of an embodiment of a collaborativerobotic system 100 including a wheeled, robotic vehicle and payloadplatform in top view.

FIG. 3 is a schematic diagram illustrative of some elements of acollaborative robotic system 100.

FIGS. 4A-4D depict illustrations of a collaborative robotic systemjointly executing a task with a human collaborator involving moving anobject through a crowded environment.

FIG. 5 depicts an illustration of the interaction between acollaborative robotic system and an object in the surroundingenvironment.

FIG. 6 illustrates a flowchart of a method 300 implementingcollaborative task execution functionality by a collaborative roboticsystem and a human collaborator as described herein.

DETAILED DESCRIPTION

Reference will now be made in detail to background examples and someembodiments of the invention, examples of which are illustrated in theaccompanying drawings.

Methods and systems for collaboration between humans and robotic systemsto jointly execute complex tasks are described herein. Collaborativetask execution takes advantage of the adaptability of humans and enablesmore effective use of a collaborative robotic system that wouldotherwise be limited to the execution of less complex tasks.

FIGS. 1 and 2 depict a side view and a top view of collaborative roboticsystem 100, respectively, in one embodiment. Collaborative roboticsystem 100 includes a wheeled, robotic vehicle 101 with one or moreactuated wheels (e.g., actuated wheels 102A-D) attached to a frame 103of the vehicle 101. In some embodiments, wheeled, robotic vehicle 101 isan omni-directional robotic vehicle capable of translating in anydirection in the xy plane and rotating about any axis parallel to thez-axis. In some of these embodiments, wheeled, robotic vehicle 101 isalso holonomic, and thus is capable of independently translating in thexy plane and rotating about any axis parallel to the z-axis. In someembodiments, the one or more actuated wheels include a mecanum wheel, anomni-directional wheel, or any combination thereof. In one embodiment,wheeled, robotic vehicle 101 employs four mecanum wheels in directdrive. Computing system 200 communicates control commands to theactuated wheels of the wheeled, robotic vehicle that cause the wheeled,robotic vehicle to move in a desired direction in the xy plane androtate about a desired axis parallel to the z-axis.

In one aspect, a collaborative robotic system includes a payloadplatform having a loading surface configured to carry a payload sharedwith a human collaborator. As depicted in FIGS. 1 and 2, collaborativerobotic system 100 also includes a payload platform 106 configured tocarry a payload 110.

In some embodiments, collaborative robotic system 100 includes one ormore payload platform actuators (not shown) attached to the frame andthe payload platform. The payload platform actuators are configured tomove the payload platform in a direction normal to the load carryingsurface 111 of the payload platform 106. In this manner, collaborativerobotic system 100 is able to adjust a height of the payload platform106 to meet the requirements of a variety of transportation tasks.

As depicted in FIG. 1, collaborative robotic system 100 includes loadsensors (e.g., load sensors 104A-D). In the embodiment depicted in FIG.1, load sensors 104A-D are coupled to payload platform 106 and frame103. In general, load sensors 104A-D may be located in any suitablelocation in a load path between payload platform 106 and the actuatedwheels (e.g., actuated wheels 102A-D). The load sensors are employed toanalyze the distribution of load on the payload platform.

In another aspect, load sensors of collaborative robotic system 100measure forces in a plane parallel to the loading surface of the payloadplatform. In the embodiment depicted in FIGS. 1 and 2, load sensors104A-D measure forces in a plane parallel to the xy plane. Signalsgenerated by load sensors 104A-D are communicated to computing system200 for further processing.

In another aspect, collaborative robotic system includes one or moreproximity sensors configured to estimate the proximity of objects to therobotic system. In general, collaborative robotic system 100 mayproximity sensors of any suitable type. By way of non-limiting example,collaborative robotic system 100 may include proximity sensors such ascapacitive sensors, Doppler effect sensors, Eddy-current sensors,inductive sensors, magnetic sensors, optical sensors, photoelectricsensors, photocell sensors, laser rangefinder sensors, passive sensors(e.g., charge-coupled devices), passive thermal infrared sensors, Radarsensors, sensors based on reflection of ionizing radiation, Sonar basedsensors, ultrasonic sensors, fiber optic sensors, Hall effect sensors,or any combination thereof. In some embodiments, proximity sensorsinclude three dimensional sensors (e.g., three dimensional LIDARsensors, stereoscopic cameras, time-of-flight cameras, monocular depthcameras, etc.) located along the perimeter of robotic system 100 (e.g.,along the front, sides, back, of robotic system 100, or any combinationthereof). In some embodiments, RGB color information is employed inconjunction with depth data to estimate the proximity of objectsrelative to robotic system 100.

Proximity sensors of collaborative robotic system 100 may be coupled tothe wheeled, robotic vehicle 101 in any suitable manner. In someexamples, the proximity sensors are coupled to frame 103. In theembodiment depicted in FIGS. 1 and 2, the proximity sensors 104A-D arecoupled to the payload platform 106. Signals generated by proximitysensors 105A-D are communicated to computing system 200 for furtherprocessing.

In some embodiments, collaborative robotic system 100 includes one ormore image capture devices (e.g., charge coupled device (CCD) camera,complementary metal on silicon (CMOS) camera, etc.) also configured toestimate the proximity of objects to the robotic system. Signalsgenerated by the image capture devices are communicated to computingsystem 200 for further processing.

FIG. 2 depicts a top view of the wheeled, robotic vehicle 101 andpayload platform 106 of collaborative robotic system 100. As depicted inFIG. 2, wheeled robotic vehicle 101 includes actuated drive wheels102A-D. The relative angular velocity of each of the actuated drivewheels 102A-D controls both the direction of the motion trajectory andthe velocity along the motion trajectory of the wheeled, robotic vehicle101. Signals generated by computing system 200 are communicated toactuated drive wheels 102A-D that causes the actuated drive wheels tomove wheeled, robotic vehicle 101 along a desired motion trajectory at adesired velocity.

In some other embodiments, one or more wheels of wheeled robotic vehicle101 are passive wheels that are free to rotate about multiple axes. Inthese embodiments, passive wheels function primarily to support the loadnormal to the ground surface, while the rotations of actuated drivewheels dictate the motion trajectory of the wheeled, robotic vehicle101. In some other embodiments, the orientation of one or more passivewheels about an axis normal to the ground surface is activelycontrolled. In these embodiments, these steering wheels also function tocontrol the direction of the motion trajectory of the wheeled, roboticvehicle 101. In some other embodiments, both the rotation of steeringwheels and the orientation of steering wheels about an axis normal tothe ground surface are actively controlled. In these embodiments,steering wheels function to control both the direction of the motiontrajectory and the velocity along the motion trajectory of the wheeled,robotic vehicle 101.

FIG. 3 is a diagram illustrative of elements of collaborative roboticsystem 100 including computing system 200, platform load sensing devices104, wheel sensing devices 107 (e.g., encoders, wheel speed sensors,etc., located at each actuated wheel), proximity sensing devices 105,image capture devices 108, and wheel actuators 102. In the embodimentdepicted in FIG. 3, computing system 200 is communicatively coupled toplatform load sensing devices 104, wheel sensing devices 107 (e.g.,encoders located at each actuated wheel), proximity sensing devices 105,image capture devices 108, and wheel actuators 102 by wiredcommunications links. However, in general, computing system 200 may becommunicatively coupled to any of the sensors and devices describedherein by either a wired or wireless communication link.

In general, any number of sensors and devices attached to collaborativerobotic system 100, including sensors and devices to interact audibly,visually, and physically with a human collaborator may also becommunicatively coupled to computing system 200.

As depicted in FIG. 3, computing system 200 includes a sensor interface210, at least one processor 220, a memory 230, a bus 240, a wirelesscommunication transceiver 250, and a controlled device interface 260.Sensor interface 210, processor 220, memory 230, wireless communicationtransceiver 250, and controlled device interface 260 are configured tocommunicate over bus 240.

Sensor interface 210 includes analog to digital conversion (ADC)electronics 211. In addition, in some embodiments, sensor interface 210includes a digital input/output interface 212. In some otherembodiments, sensor interface 210 includes a wireless communicationstransceiver (not shown) configured to communicate with a sensor toreceive measurement data from the sensor.

As depicted in FIG. 3, ADC 211 is configured to receive signals 202 fromimage capture devices 108. In another non-limiting example, ADC 211 isconfigured to receive signals 203 from proximity sensing devices 105. Inanother non-limiting example, ADC 211 is configured to receive signals204 from platform load sensing devices 104. ADC 211 is furtherconfigured to convert the analog signals 202-204 into equivalent digitalsignals suitable for digital storage and further digital processing. ADC211 is selected to ensure that the resulting digital signal is asuitably accurate representation of the incoming analog signals (i.e.,quantization and temporal discretization errors are within acceptableerror levels). In some other embodiments, image capture devices 108,proximity sensing devices 105, and platform load sensing devices 104include signal capture and processing capability on-board. In theseembodiments, image data, proximity data, and load data are communicateddigitally to computing system 200.

As depicted in FIG. 3, digital I/O 212 is configured to receive digitalsignals 201 from wheel sensing device 107. In this example, wheelsensing devices 107 include on-board electronics to generate digitalsignals 201 indicative of a measured displacement, velocity, etc., ofeach actuated wheel of wheeled robot 101. In this manner, computingsystem 200 is configured to interface with both analog and digitalsensors. In general, any of the sensors described herein may be digitalor analog sensors, and may be communicatively coupled to computingsystem 200 by the appropriate interface.

Controlled device interface 260 includes appropriate digital to analogconversion (DAC) electronics. In addition, in some embodiments,controlled device interface 260 includes a digital input/outputinterface. In some other embodiments, controlled device interface 260includes a wireless communications transceiver configured to communicatewith a device, including the transmission of control signals.

As depicted in FIG. 3, controlled device interface 260 is configured totransmit control commands 205 to one or more wheel actuators 102 thatcause the collaborative robotic system 100 to move, for example, along adesired motion trajectory. In another non-limiting example, controlleddevice interface 260 is configured to transmit command signals (notshown) to an audio output device, such as a speaker, that causes thespeaker to audibly communicate with a human collaborator. In yet anothernon-limiting example, controlled device interface 260 is configured totransmit display signals (not shown) to an image display device thatcauses the image display device to visually communicate with the humancollaborator. In general, any combination of audio/visual input andoutput devices may be contemplated to implement a natural languagecommunication interface between collaborative robotic system 100 and ahuman collaborator to facilitate collaborative task execution asdescribed herein.

Memory 230 includes an amount of memory 231 that stores sensor dataemployed by collaborative robotic system 100 to navigate an environmentwhile collaboratively executing a task with a human collaborator. Memory230 also includes an amount of memory 232 that stores program code that,when executed by processor 220, causes processor 220 to implementcollaborative task execution functionality as described herein.

In some examples, processor 220 is configured to store digital signalsgenerated by sensor interface 210 onto memory 230. In addition,processor 220 is configured to read the digital signals stored on memory230 and transmit the digital signals to wireless communicationtransceiver 250. In some embodiments, wireless communicationstransceiver 250 is configured to communicate the digital signals fromcomputing system 200 to an external computing device (not shown) over awireless communications link. As depicted in FIG. 3, wirelesscommunications transceiver transmits a radio frequency signal 252 overantenna 251. The radio frequency signal 252 includes digital informationindicative of the digital signals to be communicated from computingsystem 200 to the external computing device. In one example, sensor datagenerated by computer system 200 are communicated to an externalcomputing system (not shown) for purposes of monitoring and redirectingthe collaborative robotic system 100 based on the sensor data.

In some embodiments, wireless communications transceiver 250 isconfigured to receive digital signals from an external computing device(not shown) over a wireless communications link. The radio frequencysignals 253 includes digital information indicative of the digitalsignals to be communicated from an external computing system (not shown)and computing system 200. In one example, control commands generated byan external computing system are communicated to computer system 200 forimplementation by collaborative robotic system 100. In some embodiments,the control commands are provided to collaborative robotic system 100based on an evaluation of the collaborative task that is jointlyexecuted by collaborative robotic system 100 and a human collaborator.In some examples, an external computing system accesses additionalsensor data (e.g., image data) that is otherwise unavailable to thecollaborative robotic system 100. This additional sensor data isemployed by the external computing system to update a motion trajectoryof collaborative robotic system 100, for example, to avoid obstaclesthat are not within the field of view of collaborative robotic system100.

In one example, collaborative robotic system 100 operates with a humancollaborator to carry a large object (e.g., a desk) through a crowdedenvironment (e.g., an office). FIGS. 4A-4D depict illustrations ofcollaborative robotic system 100 jointly moving a desk 130 with a humancollaborator 120 through a crowded environment including object 125.

As depicted in FIG. 4A, robotic system 100 carries a portion of desk 130on its payload platform and human collaborator 120 carries the remainingportion of desk 130. In the scenario depicted in FIG. 4A, robotic system100 and human collaborator 120 move desk 125 in the Y-direction (i.e.,from right to left across the drawing page). Human collaborator 120provides general navigation instructions by applying forces to desk 130in a plane parallel to the XY plane. Robotic system 100 measures a forceapplied to the payload in a plane parallel to the XY plane by humancollaborator 120 based on force signals received from load sensors104A-D. Computing system 200 determines a desired movement direction tobe the direction of the measured force vector applied to the payload bythe human collaborator in the plane parallel to the XY plane. Forexample, if the force applied to desk 130 in a plane parallel to the XYplane is aligned with the Y-direction, robotic system 100 determines thedesired movement direction to be the Y-direction. However, if the forceapplied to desk 130 in a plane parallel to the XY plane is aligned withthe X-direction, robotic system 100 determines the desired movementdirection to be aligned with the X-direction.

For example, as depicted in FIG. 4A, human collaborator 120 applieslateral forces to desk 130 in a direction aligned with the Y-direction.At this instant, robotic system 100 responds by moving in theY-direction. However, as depicted in FIG. 4B, human collaborator 120applies forces to desk 130 in a direction that includes both X and Ycomponents. At this instant, robotic system 100 responds by moving in adirection aligned with the forces applied to desk 130 by humancollaborator 120.

As depicted in FIGS. 4B and 4C, the forces applied to desk 130 (i.e.,the navigational cues) by human collaborator 120 lead desk 130 on acollision course with object 125.

In another aspect, robotic system 100 overrides the navigational cues ofthe human collaborator to avoid collisions between an object in theenvironment and any of the robotic system itself, the humancollaborator, the shared payload, or any combination thereof.

As depicted in FIGS. 4A-D, robotic system 100 monitors the position ofobjects in the surrounding environment relative to the robotic system100, shared payload, and the human collaborator based on feedback fromproximity sensors 105A-D, image capture devices 108, or a combinationthereof. In the embodiment depicted in FIGS. 4A-D, robotic system 100compares the measured position of object 125 relative to two virtualboundaries 135 and 140 maintained around robotic system 100, sharedpayload 130, and human collaborator 120. Virtual boundary 135 isconsidered a “hard” boundary, i.e., robotic system 100 should notnavigate to any position that would allow an object in the surroundingenvironment to penetrate virtual boundary 135. Virtual boundary 140 isconsidered a “soft” boundary, i.e., robotic system 100 should navigateto a position that reduces the penetration of an object in thesurrounding environment within virtual boundary 140. Virtual boundaries135 and 140 are defined by predetermined threshold distance values fromrobotic system 100, shared payload 130, and human collaborator 120.Virtual boundary 140 is defined by a larger set of predeterminedthreshold distance values than virtual boundary 135.

When robotic system 100 determines that object 125 is outside of virtualboundary 140, robotic system 100 takes no obstacle avoidance measures.In these instances, robotic system 100 communicates command signals toactuated wheels 102A-D of wheeled, robotic vehicle 101 that cause thewheeled, robotic vehicle 101 to move along the movement directiondesired by human collaborator 120 as determined by the forces applied todesk 130 by human collaborator 120 as measured by load sensors 104A-D.In these instances, the velocity vector of robotic system 100, {rightarrow over (v_(r))}, is equal to the desired velocity vector asindicated by human collaborator 120, {right arrow over (v_(desired))},as indicated by equation (1).

{right arrow over (v _(r))}={right arrow over (v _(desired))}  (1)

However, when object 125 begins to impinge on virtual boundary 140,robotic system 100 behaves differently. Rather, than completelyfollowing the navigational cues provided by human collaborator 120,robotic system 100 modifies the desired trajectory to avoid collisionwith object 125. In some embodiments, a proportional control algorithmis employed as indicated by equation (2),

{right arrow over (v _(mod))}=−K _(p)(d _(buffer) −d _(OB))v{circumflexover ( )} _(x)+{right arrow over (v _(desired))}  (2)

where, {right arrow over (v_(desired))}, is the desired velocityindicated by human collaborator 120, d_(OB), is the closest distancebetween object 125 and virtual boundary 135, d_(buffer), is the distancebetween virtual boundaries 135 and 140 at the location of deepestimpingement of object 125 into virtual boundary 140, {right arrow over(v_(mod))}, is the modified velocity vector implemented by roboticsystem 100 to control the trajectory of robotic system 100, v{circumflexover ( )}_(x), is the unit vector along the normal of the surface ofobject 125 which impinges on the buffer zone between virtual boundaries135 and 140, and, K_(p), is a constant value (i.e., the proportionalgain associated with the control law indicated by equation (2)). Ingeneral, K_(p) should be selected to result in an overdamped systemresponse to maintain stability and avoid allowing robotic system 100from navigating closer to object 125 than the minimum allowed distanceto obstacles defined by virtual boundary 135. In some embodiments, thevalue of, d_(buffer), i.e., the depth of the buffer zone defined byvirtual boundaries 135 and 140, is scaled with the velocity of roboticsystem 100 in the direction of vector, v{circumflex over ( )}_(x). Inthis manner, if robotic system 100 is approaching object 125 at arelatively high rate of speed, the depth of the buffer zone is increasedto provide time to navigate around object 125. Similarly, if roboticsystem 100 is approaching object 125 at a relatively low rate of speed,the depth of the buffer zone is decreased to allow human collaborator120 to move desk 130 closer to object 125 without robotic system 100overriding the navigational cues provided by human collaborator 120.

FIG. 5 illustrates the control law indicated by equation (2). At theinstance depicted in FIG. 5, object 125 has impinged on virtual boundary140. The magnitude of the impingement is the difference between thebuffer distance, D_(buffer), and the distance between object 125 andvirtual boundary 135, D_(OB). The desired velocity, V_(desired),indicated by human collaborator 120 includes components in a direction,V_(x), normal to the surface of object 125 where it impinges on thebuffer zone between virtual boundaries 135 and 140, and a direction,V_(y), tangent to the surface of object 125 where it impinges on thebuffer zone between virtual boundaries 135 and 140. To avoid collision,the V_(y) component of V_(desired) is not a concern, but robotic system100 determines a modified control velocity, V_(mod), that counteractsthe V_(x) component of V_(desired), for example, as indicated by thecontrol law presented in equation (2).

As depicted in FIGS. 4C and 4D, robotic system 100 implements a modifiedcontrol velocity to navigate robotic system 100 and desk 130 away fromobject 125. In general, objects in the surrounding environment, e.g.,object 125, may be stationary or moving relative to ground.

FIG. 6 illustrates a flowchart of a method 300 suitable forimplementation by a collaborative robotic system as described herein. Insome embodiments, collaborative robotic system 100 is operable inaccordance with method 300 illustrated in FIG. 6. However, in general,the execution of method 300 is not limited to the embodiments ofcollaborative robotic system 100 described with reference to FIGS. 1-5.These illustrations and corresponding explanation are provided by way ofexample as many other embodiments and operational examples may becontemplated within the scope of this patent document.

In block 301, a wheeled, robotic vehicle is provided. The wheeled,robotic vehicle includes a payload platform configured to carry apayload shared with a human collaborator.

In block 302, a force applied to the payload by the human collaboratoris determined based on force signals received from one or more loadsensors.

In block 303, a desired movement direction is determined from thedetermined force applied to the payload by the human collaborator.

In block 304, a distance between an object in an environment surroundingthe human collaborator, the payload, and the wheeled, robotic vehicleand a spatial buffer zone surrounding any of the wheeled, roboticvehicle, the payload, the human collaborator, or any combinationthereof, is determined based on signals received from one or moreproximity sensors.

In block 305, a modified movement direction is determined if thedistance between the object and the spatial buffer zone is less than apredetermined threshold value.

In block 306, command signals are communicated to the one or moreactuated wheels of the wheeled, robotic vehicle that cause the wheeled,robotic vehicle to move along the modified movement direction. Themodified movement direction moves the wheeled, robotic vehicle and thepayload away from the object.

The computing system 200 may include, but is not limited to, a personalcomputer system, mainframe computer system, workstation, image computer,parallel processor, or any other computing device known in the art. Ingeneral, the term “computing system” may be broadly defined to encompassany device, or combination of devices, having one or more processors,which execute instructions from a memory medium. In general, computingsystem 200 may be integrated with a robot, such as robotic system 100,or alternatively, may be separate, entirely, or in part, from any robot.In this sense, computing system 200 may be remotely located and receivedata and transmit command signals to any element of robotic system 100.

In one or more exemplary embodiments, the functions described may beimplemented in hardware, software, firmware, or any combination thereof.If implemented in software, the functions may be stored on ortransmitted over as one or more instructions or code on acomputer-readable medium. Computer-readable media includes both computerstorage media and communication media including any medium thatfacilitates transfer of a computer program from one place to another. Astorage media may be any available media that can be accessed by ageneral purpose or special purpose computer. By way of example, and notlimitation, such computer-readable media can comprise RAM, ROM, EEPROM,CD-ROM or other optical disk storage, magnetic disk storage or othermagnetic storage devices, or any other medium that can be used to carryor store desired program code means in the form of instructions or datastructures and that can be accessed by a general-purpose orspecial-purpose computer, or a general-purpose or special-purposeprocessor. Also, any connection is properly termed a computer-readablemedium. For example, if the software is transmitted from a website,server, or other remote source using a coaxial cable, fiber optic cable,twisted pair, digital subscriber line (DSL), or wireless technologiessuch as infrared, radio, and microwave, then the coaxial cable, fiberoptic cable, twisted pair, DSL, or wireless technologies such asinfrared, radio, and microwave are included in the definition of medium.Disk and disc, as used herein, includes compact disc (CD), laser disc,optical disc, digital versatile disc (DVD), floppy disk and blu-ray discwhere disks usually reproduce data magnetically, while discs reproducedata optically with lasers. Combinations of the above should also beincluded within the scope of computer-readable media.

Although certain specific embodiments are described above forinstructional purposes, the teachings of this patent document havegeneral applicability and are not limited to the specific embodimentsdescribed above. Accordingly, various modifications, adaptations, andcombinations of various features of the described embodiments can bepracticed without departing from the scope of the invention as set forthin the claims.

What is claimed is:
 1. A collaborative robotic system comprising: awheeled, robotic vehicle including: one or more actuated wheels attachedto a frame; one or more load sensors mounted to the frame; a payloadplatform configured to carry a payload shared with a human collaborator,the payload platform coupled to the one or more load sensors; one ormore proximity sensors coupled to the frame, the payload platform, orboth; and a computing system communicatively coupled to the wheeled,robotic vehicle, the computing system configured to: determine a forceapplied to the payload by the human collaborator based on force signalsreceived from the one or more load sensors; determine a desired movementdirection from the determined force applied to the payload by the humancollaborator; determine a distance between an object in an environmentsurrounding the human collaborator, the payload, and the wheeled,robotic vehicle and a spatial buffer zone surrounding any of thewheeled, robotic vehicle, the payload, the human collaborator, or anycombination thereof, based on signals received from the one or moreproximity sensors; determine a modified movement direction if thedistance between the object and the spatial buffer zone is less than apredetermined threshold value; and communicate command signals to theone or more actuated wheels of the wheeled, robotic vehicle that causethe wheeled, robotic vehicle to move along the modified movementdirection, wherein the modified movement direction moves the wheeled,robotic vehicle and the payload away from the object.
 2. Thecollaborative robotic system of claim 1, wherein the one or more loadsensors measure force in a direction parallel to a load carrying surfaceof the payload platform.
 3. The collaborative robotic system of claim 1,wherein the one or more actuated wheels include a mecanum wheel, anomni-directional wheel, or any combination thereof.
 4. The collaborativerobotic system of claim 1, further comprising: one or more payloadplatform actuators attached to the frame and the payload platform, theone or more payload platform actuators configured to move the payloadplatform in a direction normal to a load carrying surface of the payloadplatform.
 5. The collaborative robotic system of claim 1, wherein theobject in the environment is moving.
 6. The collaborative robotic systemof claim 1, further comprising: one or more image capture devices,wherein the determining of the distance between the object in theenvironment and the spatial buffer zone is also based on imageinformation received from the one or more image capture devices.
 7. Thecollaborative robotic system of claim 1, wherein the computing system isfurther configured to: communicate command signals to the one or moreactuated wheels of the wheeled, robotic vehicle that cause the wheeled,robotic vehicle to move along the desired movement direction if thedistance between the object and the spatial buffer zone is greater thanthe predetermined threshold value.
 8. A method comprising: providing awheeled, robotic vehicle having a payload platform configured to carry apayload shared with a human collaborator; determining a force applied tothe payload by the human collaborator based on force signals receivedfrom one or more load sensors; determining a desired movement directionfrom the determined force applied to the payload by the humancollaborator; determining a distance between an object in an environmentsurrounding the human collaborator, the payload, and the wheeled,robotic vehicle and a spatial buffer zone surrounding any of thewheeled, robotic vehicle, the payload, the human collaborator, or anycombination thereof, based on signals received from one or moreproximity sensors; determining a modified movement direction if thedistance between the object and the spatial buffer zone is less than apredetermined threshold value; and communicating command signals to theone or more actuated wheels of the wheeled, robotic vehicle that causethe wheeled, robotic vehicle to move along the modified movementdirection, wherein the modified movement direction moves the wheeled,robotic vehicle and the payload away from the object.
 9. The method ofclaim 8, wherein the one or more load sensors measure force in adirection parallel to a load carrying surface of the payload platform.10. The method of claim 8, wherein the object in the environment ismoving.
 11. The method of claim 8, wherein the determining of thedistance between the object in the environment and the spatial bufferzone is also based on image information received from one or more imagecapture devices.
 12. The method of claim 8, further comprising:communicating command signals to the wheeled, robotic vehicle that causethe wheeled, robotic vehicle to move along the desired movementdirection if the distance between the object and the spatial buffer zoneis greater than the predetermined threshold value.
 13. The method ofclaim 8, wherein the determining of the modified movement direction isbased on a magnitude of impingement of the object into the spatialbuffer zone.
 14. A collaborative robotic system comprising: a wheeled,robotic vehicle including: one or more actuated wheels attached to aframe; one or more load sensors mounted to the frame; a payload platformconfigured to carry a payload shared with a human collaborator, thepayload platform coupled to the one or more load sensors; one or moreproximity sensors coupled to the frame, the payload platform, or both;and a non-transitory, computer-readable medium storing instructions thatwhen executed by a computing system cause the computing system to:determine a force applied to the payload by the human collaborator basedon force signals received from the one or more load sensors; determine adesired movement direction from the determined force applied to thepayload by the human collaborator; determine a distance between anobject in an environment surrounding the human collaborator, thepayload, and the wheeled, robotic vehicle and a spatial buffer zonesurrounding any of the wheeled, robotic vehicle, the payload, the humancollaborator, or any combination thereof, based on signals received fromthe one or more proximity sensors; determine a modified movementdirection if the distance between the object and the spatial buffer zoneis less than a predetermined threshold value; and communicate commandsignals to the one or more actuated wheels of the wheeled, roboticvehicle that cause the wheeled, robotic vehicle to move along themodified movement direction, wherein the modified movement directionmoves the wheeled, robotic vehicle and the payload away from the object.15. The collaborative robotic system of claim 14, wherein the one ormore load sensors measure force in a direction parallel to a loadcarrying surface of the payload platform.
 16. The collaborative roboticsystem of claim 14, wherein the one or more actuated wheels include amecanum wheel, an omni-directional wheel, or any combination thereof.17. The collaborative robotic system of claim 14, further comprising:one or more payload platform actuators attached to the frame and thepayload platform, the one or more payload platform actuators configuredto move the payload platform in a direction normal to a load carryingsurface of the payload platform.
 18. The collaborative robotic system ofclaim 14, wherein the object in the environment is moving.
 19. Thecollaborative robotic system of claim 14, further comprising: one ormore image capture devices, wherein the determining of the distancebetween the object in the environment and the spatial buffer zone isalso based on image information received from the one or more imagecapture devices.
 20. The collaborative robotic system of claim 1, thenon-transitory, computer-readable medium further storing instructionsthat when executed by a computing system cause the computing system to:communicate command signals to the one or more actuated wheels of thewheeled, robotic vehicle that cause the wheeled, robotic vehicle to movealong the desired movement direction if the distance between the objectand the spatial buffer zone is greater than the predetermined thresholdvalue.